Computational Methods and Clinical Applications in Musculoskeletal Imaging 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers /

This book constitutes the refereed proceedings of the 5th International Workshop and Challenge on Computational Methods and Clinical Applications for Musculoskeletal Imaging, MSKI 2017, held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 13 workshop papers were c...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Glocker, Ben (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Yao, Jianhua (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Vrtovec, Tomaž (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Frangi, Alejandro (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Zheng, Guoyan (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
Έκδοση:1st ed. 2018.
Σειρά:Computer Communication Networks and Telecommunications ; 10734
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Localization of Bone Surfaces from Ultrasound Data Using Local Phase Information and Signal Transmission Maps
  • Shape-aware Deep Convolutional Neural Network for Vertebrae Segmentation
  • Automated Characterization of Body Composition and Frailty with Clinically Acquired CT
  • Unfolded cylindrical projection for rib fracture diagnosis
  • 3D Cobb Angle Measurements from Scoliotic Mesh Models with Varying Face-Vertex Density
  • Automatic Localization of the Lumbar Vertebral Landmarks in CT Images with Context Features
  • Joint Multimodal Segmentation of Clinical CT and MR from Hip Arthroplasty Patients
  • Reconstruction of 3D muscle fiber structure using high resolution cryosectioned volume
  • Segmentation of Pathological Spines in CT Images Using a Two-Way CNN and a Collision-Based Model
  • Attention-driven deep learning for pathological spine segmentation
  • Automatic Full Femur Segmentation from Computed Tomography Datasets using an Atlas-Based Approach
  • Classification of Osteoporotic Vertebral Fractures using Shape and Appearance Modelling
  • DSMS-FCN: A Deeply Supervised Multi-Scale Fully Convolutional Network for Automatic Segmentation of Intervertebral Disc in 3D MR Images.